Improving prediction of drug therapy outcome via integration of time series gene expression and Protein Protein Interaction network

Liwei Qian, Hao-ran Zheng
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引用次数: 1

Abstract

Drug therapy to patients is often with partial success, and has been associated with a number of adverse reactions. Prediction of patients' response to therapy at the early stage of the treatment is crucial to avoiding those unnecessary adverse reactions. In this paper, a new approach that integrates time series gene expression and Protein Protein Interaction (PPI) network is presented to improve the prediction of patients' response to drug therapy. Experimental results showed that our method outperformed previous approaches. The method proposed here offers a huge potential for applications in pharmacogenomics and medicine.
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通过整合时间序列基因表达和蛋白-蛋白相互作用网络提高药物治疗结果预测
对患者的药物治疗通常是部分成功的,并且与一些不良反应有关。在治疗早期预测患者对治疗的反应对于避免不必要的不良反应至关重要。本文提出了一种将时间序列基因表达与蛋白蛋白相互作用(Protein Protein Interaction, PPI)网络相结合的新方法,以提高对患者药物治疗反应的预测。实验结果表明,我们的方法优于以往的方法。本文提出的方法在药物基因组学和医学领域具有巨大的应用潜力。
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